Consumer Purchase Intention and Purchase Behaviour for Green Fast Moving Consumer Goods

Keywordsfast-moving consumer goods green products purchase behaviour purchase intention Theory of Planned Behaviour

JEL Classification M31, O33, Q56

Full Article

1. Introduction

Environmental sustainability has risen to the top of the world’s social agenda in recent decades, and is now regarded as a significant engine for innovation. As a result, the number of businesses creating green products is fast expanding, and customers are becoming more interested in them. According to Joshi and Rahman (2015), environmentally responsible purchasing is vital, as the unplanned purchase of certain goods can severely damage the environment. Consumers are thus considered to hold the capability to prevent or decrease environmental damage by purchasing green products. Yadav and Pathak (2017) believe that an individual’s green consumption behaviour could be an effective way to minimise the negative impacts of consumption on the environment. Since the early 1990s, studies have investigated the purchasing behaviour of green consumers or the motives for buying green products (Ritter et al., 2015; Suki, 2016). However, many of these studies were viewed from the context of developed countries. As such, there has been a gap in the literature in understanding consumer green purchase behaviour in developing countries such as South Africa. From a marketing perspective, this study envisages that understanding consumer purchase intention towards green products, particularly FMCGs that are green, is important.

Retail goods that are consumed quickly are referred to as FMCG. The specific characteristic of FMCGs is that most consumers regularly purchase and consume these products in their daily lives and that these products are normally low-involvement products (Dwivedi and McDonald, 2018). FMCGs are usually everyday low-priced, low-risk products that are consumed within a short time period and require very little thought when purchasing (Makhutla, 2014). Worldwide, the consumer packaged goods market, in 2019, was estimated to be worth $8tn and was expected to grow to $14tn by 2025 (McKinsey, 2020). In South Africa, the FMCG industry had surpassed a trillion Rands based on 2011 estimates, and the industry grew in volume by an average of 3.45% in nominal terms over the period of 2012-2016 (PWC, 2012). Hence, one could reasonably assume that the FMCG landscape in South Africa is maturing and changing with the introduction of new platforms and retail outlets. For example, there has been an increase in the numbers of convenience stores, more discount retailers and online shopping across the country (Van Niekerk, 2018).

Despite the laudable economic contribution of the FMCG sector to South Africa's economy, it must be noted that most FMCG companies are process-based, creating large volumes of waste with disposal at various stages, from production, in the supply chain process, to consumption (Makhutla, 2014). From an environmental perspective, Martin-Rios et al. (2018) point out that waste management is the key to the green initiative and believe that manufacturers, wholesalers, and retailers of FMCGs have a social responsibility towards the environment. According to Niedermeier et al. (2021), green FMCGs can replace conventional FMCGs, which are often based on fossil resources. Green FMCG products range from non-food FMCGs such as batteries (Coskun et al., 2017), tissue papers (Barbarossa and De Pelsmacker, 2016), sanitary pads (Cha and Park, 2019), biocosmetics (Liobikiene and Bernatoniene, 2017), biofuels, electrical cars, or green textiles to a broad variety of FMCGs to food and beverages (Buder et al., 2014; Schäufele and Hamm, 2018).

Compared to conventional FMCG products, green FMCGs differ not only in how often they are used and bought but also the nature of the act of their consumption, the intention of consumers while enacting their product choices or the effects that consumers expect when buying these products (Giulio et al., 2014). It is for this reason that environmentally friendly product features could trigger an interesting buying impulse. For this reason, Makhutla (2014) states that many of the FMCG companies are beginning to take steps towards ensuring that their products are produced in line with environmentally friendly conditions. Consequently, there is a paradigm shift in green consciousness as companies are moving from reducing pollution directly to changing their product design (Baqer, 2012). In addition, Zhang and Dong (2020) note that companies are avoiding products that are polluting the environment or harmful to human health and turning to environmental-protection products.

Although pro-environmental sentiments are one of the most important influencing elements of pro-environmental behaviour, Niedermeier et al. (2021) argue that such beliefs may not necessarily translate to environmentally friendly buying behaviour. Owing to this and given the fact that other variables may have a role in this process, it becomes useful to look at the factors that influence customers' decisions to buy green products and the actual purchase behaviour. This study, therefore, aims to test the applicability of green consumption of FMCG products grounded in the Theory of Planned Behaviour (TPB) and thus address the “attitudes–behaviour” gap documented in the literature from the perspective of South African consumers.

2. Theoretical Framework

According to Zhang and Dong (2020), environmental behaviour has applicability when it comes to the analysis of green purchase behaviour. Green purchase forms part of private environmental behaviour. Accordingly, academics have approached consumer theory through the lens of psychology and the interaction of internal and external influences. Green consumer theories based on psychology hold the belief that consumers’ pro-environmental behaviour is primarily influenced by psychological factors, with a focus on the impact of perceived behavioural regulation, attitude, beliefs, moral standards, and other factors impacting on consumers' purchasing intention or behaviour for green goods (Zhang and Dong, 2020). While there are several consumer theories such as the Value-Attitude-Behaviour (VAB) model, Value-Norm-Belief (VNB) theory of Environmentalism, the integrated model, the Attitude-Behaviour-condition (ABC) Model as reported in the literature, the TPB remains one of the most common and effective theories for studying pro-environmental behaviour (Nimri et al., 2020; Rahman and Reynolds, 2019).

TPB has a simple structure that allows for a thorough study of the development of intentions and behaviour by considering both volitional and non-volitional elements simultaneously (Ajzen, 2020). The TPB paradigm, according to the seminal work of Ajzen (1991), considers behaviour as a feature of salient beliefs (indirect constructs of the theory) that are relevant to the behaviour. Individuals may have a variety of beliefs about any given action, but only the most important beliefs can influence their behavioural intentions (Ajzen, 2020). 

To this end, several empirical studies have demonstrated the effectiveness of TPB's interpretation of behaviour (Moser, 2015; Yadav and Pathak, 2017), and it has since become the most common theory for studying green purchasing behaviour (Zhang and Dong, 2020). Rezai et al. (2012), for example, used TPB to study Malaysian consumers' green food purchasing behaviour, and their empirical findings indicate that attitude, subjective norms, and perceived behavioural control are the key factors influencing purchase behaviour. Judge et al. (2019) obtained similar results when they investigated customer purchases of green housing.Based on this, the TPB was streamlined in this study to measure the factors influencing the purchase intention as well as the actual purchase behaviour of FMCG green products.

3. Conceptual Framework and Hypotheses Development

The following section presents the conceptual framework and the hypotheses were developed for this study.

3.1 The Perceived Role of Pro-Environmental Attitude on Green Purchase Intention

According to Zhang and Dong (2020), psychological variables are composed mainly of attitudes, environmental consciousness, values and beliefs. Psychological variables have a profound effect on consumer behaviour, which could result in significant differences in consumers' purchase intention. Green consumers are often described as consumers who have a positive attitude towards the environment. Green consumers therefore engage in activities that minimise harm to the environment through their consumption or even support it through their consumption (Ertz et al., 2016). Several recent studies had shown the positive influence of pro-environmental attitudes on the purchase behaviour of green products (Chekima et al., 2016; Klein et al., 2020; Mishal et al., 2017; Robinot et al., 2017 and Scherer et al., 2018). Niedermeier et al. (2021) explain that the feeling of being able to do something positive for the environment usually motivates consumers to purchase green products. It therefore becomes critical to establish the factors that influence green product purchase, in this instance, among South African consumers. According to Rathod (2018), consumers, in a number of cases, buy and use different products based on their perception of these products. Thus, in the light of the literature, it is hypothesised:

H1: There is a positive relationship between the perceived pro-environmental attitudes and green purchase intention.

3.2 The Perceived Role of Values (Quality) and Lack of Trust in Green Products on Green Purchase Intention

According to Cheung and To (2019), certain attributes of the green product such as the level of quality, degree of aesthetics, and the number of functions may influence consumers' attitudes towards the purchase of such products. Since green products consume less energy or resources, consumers believe that the use of such products could be beneficial to, as well as strengthen favourable attitudes towards environmental protection. More so, it is reasonable to agree that the value gained on saving energy and resources could influence a drive to purchase green products. Nonetheless, the aforementioned authors caution that regardless of the environmental intention of the consumers, if green products are of a lower quality than the conventional ones, consumers may purchase fewer green products as they may find no substantial difference in using green products compared to conventional products (Cheung and To, 2019).

Equally, according to Niedermeier et al. (2021), the doubt in consumers' minds that a product is sustainable or that it is less effective than the conventional product can be an obstacle to purchasing a green product. This view aligns with Joshi and Rahman (2015) that a lack of trust can act as a purchase barrier to green products. It is therefore hypothesised:

H2: There is a positive relationship between the perceived pro-environmental attitudes and green purchase intention.

3.3 The Perceived Role of Price on Green Purchase Intention

The cost of a green product may present itself as a barrier to consumer purchase. Whilst it may be correct to assume that a higher price may not be the sole barrier to green product purchase, several authors believe that the high cost of green products may deter people from purchasing them (Barber et al., 2014; Liobikiene and Bernatoniene, 2017). More so, it has been found that some consumers view the price of green products as being more expensive than conventional ones (Chang, 2011). Regardless of the price, other scholars have argued that many environmental-friendly convinced consumers will pay a higher price for green products due to their health and environmental benefits (Davari and Strutton, 2014; Kainz, 2016; Scherer et al., 2018). Others argue that consumers, in some cases, expect to pay higher prices for green products and trust them less when they have a lower price (Kahraman and Kazançoglu, 2019). In South Africa, for example, the consumer market is characterised by consumers who are price sensitive, prioritising value for money as a driver of choice (Van Niekerk, 2018). As a result, the industry frequently has discounted pricing to attract consumers in the hope of higher purchase volumes (Van Niekerk, 2018). Hence, understanding consumers’ perception of a given product in terms of its price will be critical in promoting green consumption. It is thus hypothesised:

H3: There is a positive relationship between the perceived product price and green purchase intention.

3.4 The Relationship between Green Purchase Intention and Actual Purchase Behaviour

Forsberg and Löfvenberg (2011) describe green consumers as environmentally conscious consumers who buy, are willing to, or say that they will be buying socially desirable FMCGs. Jaiswal et al. (2020) indicate that green consumers are normally involved in the purchase and consumption of products considered green, environmentally friendly, and sustainable. Of interest to this study, and as argued by Handayani (2017), the joiurney to environmental awareness of actual green consumption and behaviour is not straightforward. Consumers may be willing to buy sustainable products, but very few realise their purchase intention. Thus, in the light of the existing literature, it is hypothesised:

H4: There is a positive relationship between the perceived purchase intention and actual purchase behaviour of green products.

The above-hypothesised relationships can be depicted in the conceptual model reflected in Figure 1. The conceptual model is a representation of the main constructs of this study and their relationships with one another. In this model, perceived pro-environmental attitude, perceived value (quality), and perceived price are the predictor variables while customer purchase intention is the mediating variable. The customer's actual purchase behaviour is the outcome variable.

Figure 1: Conceptualized research model

4. Research Methodology

A quantitative research approach that followed a descriptive and cross-sectional research design was adopted in the study. Acording to Punch (2005), a quantitative approach responds to research inquiry using numerical data. Shukla (2008) notes that the quantitative research approach is associated with a cross-sectional survey and uses a descriptive research approach. The target population for this study are residents over the age of 18 in the greater Durban area of the KwaZulu-Natal province, South Africa. A non-probability, convenience sampling method was employed. The measuring instrument was informed, based on studies by Unnamalai (2016), Niedermeier et al. (2021), Prakash and Pathak (2017), Jaiswal et al. (2020) and (Yadav and Pathak, 2017).

Owing to COVID-19 restrictions, data was collected online. 500 questionnaires were despatched to individuals in the greater Durban area. In total, 381 completed questionnaires were received. The necessary ethical protocols were observed.

5. Results

5.1 Socio-Demographic Characteristics

The socio-demographic characteristics of the respondents are provided in Table 1. It emerged that the majority of the respondents were female (60.4%), within 25-34 years of age (44.1%), earning an average income of between R10000 –R29999 (41.2%), and mainly residing in the sub-urban area of Durban.

Table 1: Respondents socio-demographic characteristics

5.2 Scale Reliability and Construct Validity of the Measurement Model

Structural equation modelling (SEM) was used to test the proposed model. The testing of the proposed measurement model was carried out in two stages. The first stage entailed testing the measurement model and confirming the validity and reliability of the measurement model. The stage entailed testing the structural path model. At both stages, the model fit indices were found to test the adequacy of the models (measurement and structural).

Using AMOS 27 software and Statistical Package for Social Science (SPSS version 27), both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to assess the dimensionality, reliability and validity of the constructs. The scale reliability of the five constructs was tested using Cronbach’s alpha. Cronbach’s alpha measured for the five constructs ranged from 0.784-0.988, reported in Table 2. This met the condition for internal consistency of the scale reliability according to Hair et al. (2015). In addition, the mean value measured for the items in each of the constructs was above 3. The mean value measured for perceived intention ranged from 4.02 to 4.28, perceived value ranged from 3.98 to 4.22, perceived price ranged from 3.85 to 3.95, actual purchase behaviour ranged from 3.91 to 3.93, and perceived attitude were all 3.82, which suggests that there was strong agreement in all the items in the constructs.

Table 2: Factor loading coefficient, Cronbach’s alpha, the mean and standard deviation of the constructs

The construct validity of the measurement model is reported in Table 3. The construct validity was assessed by estimating the measures of convergent and discriminant validity. This includes all measurement items and latent variables, the items' loadings, composite reliability, average variance extracted (AVE), and maximum shared square variance (MSV). The analysis is done using CFA to explore the measurement of the latent constructs as achieved using the measured variables (Everitt and Skrondal, 2010). Convergent validity is attained when composite reliability is greater than the average variance extracted (AVE) and when the AVE is greater than 0.5 (Mimouni-Chaabane and Volle, 2010). Similarly, discriminant validity is attained when AVE is greater than maximum shared square variance (MSV). All latent variables have AVE values in the range of 0.567-0.966 range, which is above the threshold of 0.5 (Mimouni-Chaabane and Volle, 2010). This suggests that all latent variables have an acceptable level of convergent validity. Since the value of the AVE for each construct is greater than MSV values, it can be said that the latent variables have adequate discriminant validity. The composite reliability of all constructs is greater than the 0.70 threshold, thus suggesting acceptable reliability (Alalwan et al., 2018). It can therefore be said that the construct validity of the measurement model can be regarded as good.

Table 3: Composite reliability, average variance extracted, and maximum shared square values

The overall fit of the model was assessed by multiple fit criteria. The normed chi-square (cmindf) is an absolute fit index that is obtained by dividing χ²by df. It is recommended that for a cmindf to be acceptable, the value should be greater than one but less than five (Hair et al., 2015). Another fit index used is the Goodness of fit index (GFI). Hu and Bentler (1999) recommend a GFI value of ≥0.9. The third fitness index used is the Comparative fit index (CFI). Alalwan et al. (2018) suggest an acceptable value to be ≥0.9. The Tucker–Lewis index (TLI) was also used to assess the fitness of the model. Hair et al. (2015) recommend a cut off value for the TLI to be ≥0.9. The final fit index used is the Root mean square error of approximation (RMSEA). The RMSEA value is recommended to be between 0.05 and 0.08 (Mimouni-Chaabane and Volle, 2010). The model fit indices are as follows: Chi-square = 188.241; df = 80; cmindf=2.353; CFI = 0.986; GFI=0.940; TLI = 0.981; RMSEA =0.060, which suggests that the measurement model is acceptable.

5.3 Hypothesis Testing

The second stage of the data analysis involved converting the measurement model found in stage 1 into a path model that shows the relationships between the latent variables (Figure 2). This path model is then used to test the effect of the independent variables (IVs) on the dependent variables (DVs). An SEM was also employed to test all the hypothesized relationships that exist among the latent variables. This was utilized given that SEM allows simultaneous evaluation of multiple related independent and dependent relationships and considers measurement estimates among the constructs (Hair et al., 2009). The resulting SEM with estimated standardized relationships is given in Figure 2. The goodness-of fitness indices are as follows: chi-square = 188.241; df = 80; cmindf=3.366; CFI = 0.974; GFI=0.914; TLI = 0.967; RMSEA =0.079, which suggests that the measurement model is acceptable.

Figure 2: SEM model showing the relationship among the constructs in the proposed model

Table 4: Path regression estimates of the proposed model

6. Discussion

6.1 Theoretical Contribution

This study aimed to test the applicability of green consumption of FMCG products grounded in TPB and thus address the “attitudes–behaviour” gap documented in the literature from the perspective of South African consumers. In this, we developed and tested a model of three predictors of green purchase intention, which is linked in turn to green purchase behaviour. In line with the study hypotheses, and except perceived price, the results from the structural equation model confirmed significant positive relationships between two of the predictors of the green purchase intention, as well as between the green purchase intention and actual purchase behaviour.

The findings of this study are in agreement with the growing body of literature on green purchase behaviour by showing that consumers' perceived pro-environmental attitudes, perceived value (quality) of green FMCG products positively influences their green purchase intention, which further mediates the relationship with actual purchase behaviour. The findings of this study are consistent with other scholars’ models such as Nguyen et al. (2016), Yadav and Pathak (2017), and more recently Hojnik et al. (2020). Thus, the findings contribute to the growing research into green purchase intention and behaviour that is anchored in Azjen's TPB. This study, therefore, tested and conceptually extended the TPB first proposed by Azjen in the context of green FMCG consumption in the context of a developing country. The model also revealed the importance of price in green purchase intention and corroborates with other scholars who note the high price of green products may become a barrier to consumer purchase intention. Overall, the findings of this study suggest that the TPB model can be streamlined to study the attitude-behaviour gap of green FMCG products as it provides a robust explanation of green FMCG actual purchase behaviour.

6.2 Practical Implications

Extant literature suggests that individuals’ green consumption habits could effectively minimise the negative impact of consumption on the environment. While studies in the past on green FMCG purchase intention and behaviour of consumers were mostly done in the context of developed countries (Niedermeier et al., 2021), there has been a gap in the literature in understanding consumer green purchase behaviour from that of a developing country like South Africa. More particularly, and from South African marketers’ perspective, understanding the consumers' purchase intention towards Fast-moving consumer goods that are green, is important. This is particularly useful as it could help in eliminating the obstacles facing South African consumer green consumption habits. This study provides practical implications for FMCG companies in their bid to shift from conventional products to green products.

Hojnik et al. (2020) note that the demand for products that not only satisfy a consumer's immediate needs but also benefits the environment in the long term is on the rise. As such, there has been increasing interest among scholars on the actual purchase behaviour of green consumers or the motives for buying green products (Ritter et al., 2015; Suki, 2016). It is argued that consumers simultaneously consider both the benefits and the environmental impacts of products they intend to purchase (Hojnik et al., 2020). This means that a product with a negative impact on the environment may be avoided, as can a product that does not satisfy the customer’s needs and wants even though it is environmentally friendly. Consistent with this, it emerged from the study that green consumers consider the environmental consequence as well as the value (quality) of the products in their purchase intention.

Although pro-environmental sentiment is one of the most important factors underlying consumer behaviour, Niedermeier et al. (2021)argue that such beliefs may not necessarily translate into environmentally friendly buying behaviour. Nevertheless, the finding of this study suggests that consumers' purchase intention for green FMCG products results in actual behaviour. It was found that green consumers are driven into purchasing green FMCG products through green purchase intention, which in turn is driven by their pro-environmental attitudes and the perception of the value (quality) of FMCG products.

Furthermore, the findings of this study in terms of the influence of pro-environmental attitudes and purchase intention concur with other scholars who had found a positive influence of pro-environmental attitudes on the purchase behaviour of green products(Klein et al., 2020; Robinot et al., 2017; Scherer et al., 2018). The plausible explanation for this could be linked to the feeling of being able to do something positive for the environment. This can be corroborated by Niedermeier et al. (2021)who believe that the feeling of being able to do something for the environment usually leads consumers to take the impact of their purchases on the environment into account and thus usually leads to a higher awareness of their environment. Equally, Hsu et al. (2017) note that increased community awareness and policies concerning environmental matters have changed consumers' behaviours and induced purchasing decisions for green products.

Another useful insight to the drivers of green FMCG purchase intention is the value and or quality the green consumers attached to the products. Ottman and Mallen (2014) reported that green products are healthy and are of higher quality when compared to conventional products. The value green consumers have for green FMCG, particularly the perceived health benefits derived from green FMCG might have influenced their purchase intention. This is corroborated by the findings of Razaa et al. (2020) that consumer perceived values play an important role in developing their purchase behaviour towards green products. The findings also concur with those of Yadav and Pathak (2017) who found that perceived values positively influence consumers’ intention to purchase green products.

Previous scholars have reported that environmentally-friendly consumers will pay a premium for green products due to the health and environmental benefits of these products (Davari and Strutton, 2014; Kainz, 2016; Scherer et al., 2018).  Nevertheless, it is noteworthy that although South African consumers are conscious of the environmental value of green FMCG products, they may not be willing to pay more for these products. This finding may be attributed to the price sensitivity of local consumers, who prioritise value for money as a driver of choice (Van Niekerk, 2018). Marketers, as well as companies that offer green products, must, therefore, rethink their strategies, especially with respect to the pricing of green FMCG products. More specifically, companies should invest more in offering “special price sales” to attract more consumers to drive their green vision. This is important, particularly as corporate social responsibility for manufacturers, wholesalers, and retailers of FMCG products in ensuring the environmental sustainability of the products through the consumption habits of their consumers (Martin-Rios et al., 2018).

6.3 Limitations and Directions for Future Research

While the study has wider applicability in the understanding of green FMCG products purchase intention and actual purchase behaviour from a South African perspective, it must be noted that it was limited to the Greater Durban area which may affect its generalizability. Hence, further research could be carried out in other provinces in South Africa to gain a more holistic view of green consumer purchasing intention and the actual behaviour towards green FMCG products. Another limitation of the study is that the researcher used convenience sampling through the use of the researcher's social media contact list. This may have some form of bias and could lead to respondents adjusting their answers to appear to be politically correct or socially acceptable, as found by Park et al.(2012). Nevertheless, the researcher tried to avoid the presumed biases by providing full anonymity to the respondents. Moreover, it is acknowledged in the literature that the socio-demographic characteristics of green consumers significantly affect both green purchase intentions and actual purchase behaviour (Hojnik et al., 2020). Future studies could investigate and incorporate socio-demographic characteristics of green consumers as a determinant in terms of the TPB model.

7. Conclusion

The study has examined the applicability of the TPB model (attitude–intention–behaviour) in understanding green consumer purchase intention and actual purchasing behaviour of green FMCG. As such, the study extends Ajzen's TPB (1991) model by modifying it to fit the context of green purchase intention and actual purchase behaviour of FMCG in a developing country. In the study, the researchers proposed and tested a model on a sample of 381 green consumers over 18 years of age. The data indicates that consumers’ pro-environmental attitudes, perceived value (quality) influence their green purchase intention of FMCG products. The study also found that green purchase intentions directly translate to the actual purchase behaviour of FMCG products. Nevertheless, marketers, retailers and manufactures in South Africa must understand the fact that the price of green FMCG products may serve as a barrier to the consumption of green FMCG products. This is important if they hope to achieve their social corporate responsibility to the environment by driving in green consumption habits among South African consumers who are generally price sensitive.

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Acknowledgment:The authors acknowledge the financial support and assistance provided by the Faculty of Management Sciences, Durban University of Technology, South Africa.

Conflicts of Interest: The author states that they have no conflicts of interest.

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